Subcutaneous ocrelizumab in multiple sclerosis: Results of the Phase 1b <scp>OCARINA</scp> I study
Bibliographic record
Abstract
OBJECTIVE: Subcutaneous ocrelizumab is being developed to provide treatment flexibility and additional choice to patients with multiple sclerosis. OCARINA I (NCT03972306) is an open-label, multicenter, Phase 1b, dose-finding study to investigate the pharmacokinetics, safety, tolerability, and immunogenicity of subcutaneous ocrelizumab and to select a dose for the Phase 3 OCARINA II study (NCT05232825). METHODS: Patients with relapsing or primary progressive multiple sclerosis (aged 18-65 years; Expanded Disability Status Scale score 0.0-6.5) were enrolled into two groups: previously treated with intravenous ocrelizumab (Group A) or naïve to ocrelizumab (Group B). Patients received single ascending doses of subcutaneous ocrelizumab up to 1200 mg. Following dose escalation, new patients in Group A were randomized (1:1) to receive a single 600 mg intravenous ocrelizumab dose or the candidate subcutaneous dose, which was predicted to result in similar exposure as the 600 mg intravenous dose while being safe and well tolerated. The area under the concentration-time curve for both formulations was used to select the subcutaneous ocrelizumab dose. Patients in all cohorts could enter a dose-continuation phase. RESULTS: Eighty-eight and 47 patients were enrolled into Group A and B, respectively; most patients were female (72.7%/63.0%), and mean age at baseline was 45.7 and 39.7 years, respectively. Subcutaneous ocrelizumab was well tolerated across all doses tested. The 920 mg subcutaneous ocrelizumab dose was selected for the OCARINA II study based on pharmacokinetic and safety data. INTERPRETATION: Subcutaneous ocrelizumab may provide patients with multiple sclerosis with an additional treatment option.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".